code: def init_torch_weight_const(m, val):
      for p in m.parameters():
          if p.dim() > 1:
              p.data.fill_(val)
  
imports: from __future__ import division
  import argparse
  import importlib
  import os
  import tempfile
  from test.utils_test import make_dummy_json_st
  import chainer
  import numpy
  import pytest
  import torch
  from espnet.nets.pytorch_backend.nets_utils import pad_list
  from espnet.utils.training.batchfy import make_batchset
label_desc: Use image node_id 9 for calling a global function with example usage: init_torch_weight_const(m, val) without return types